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  • Open Access

    ARTICLE

    Ensemble Voting-Based Anomaly Detection for a Smart Grid Communication Infrastructure

    Hend Alshede1,2,*, Laila Nassef1, Nahed Alowidi1, Etimad Fadel1

    Intelligent Automation & Soft Computing, Vol.36, No.3, pp. 3257-3278, 2023, DOI:10.32604/iasc.2023.035874

    Abstract Advanced Metering Infrastructure (AMI) is the metering network of the smart grid that enables bidirectional communications between each consumer’s premises and the provider’s control center. The massive amount of data collected supports the real-time decision-making required for diverse applications. The communication infrastructure relies on different network types, including the Internet. This makes the infrastructure vulnerable to various attacks, which could compromise security or have devastating effects. However, traditional machine learning solutions cannot adapt to the increasing complexity and diversity of attacks. The objective of this paper is to develop an Anomaly Detection System (ADS) based on deep learning using the… More >

  • Open Access

    ARTICLE

    A Hybrid Model for Anomalies Detection in AMI System Combining K-means Clustering and Deep Neural Network

    Assia Maamar1,*, Khelifa Benahmed2

    CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 15-39, 2019, DOI:10.32604/cmc.2019.06497

    Abstract Recently, the radical digital transformation has deeply affected the traditional electricity grid and transformed it into an intelligent network (smart grid). This mutation is based on the progressive development of advanced technologies: advanced metering infrastructure (AMI) and smart meter which play a crucial role in the development of smart grid. AMI technologies have a promising potential in terms of improvement in energy efficiency, better demand management, and reduction in electricity costs. However the possibility of hacking smart meters and electricity theft is still among the most significant challenges facing electricity companies. In this regard, we propose a hybrid approach to… More >

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